best-of-python-dev: a generated ranking of 270 Python developer tools, and how to read it
🏆 A ranked list of awesome python developer tools and libraries. Updated weekly.
At a glance
- What is it?
- The repository is a weekly-regenerated list of Python tooling, ranked by an automated project-quality score across 17 categories. Its value is the metadata and the machine-readable projects.yaml; its weakness is that the ranking number is opaque and the entries are pointers, not evaluations.
- Who is it for?
- Use best-of-python-dev as a discovery index and as a machine-readable inventory of Python tooling, especially if you want the projects.yaml file rather than the rendered page. Do not use it as a substitute for evaluating a specific tool, and do not treat the quality score as a verdict.
- Can I use it commercially?
- Yes, with credit. CC-BY-SA-4.0 allows commercial use as long as you credit the authors and indicate what you changed. It is written for creative content, so check how it applies to any code.
- Is it still maintained?
- Yes. The repository last received commits 5 days ago.
- What is it written in?
- Mainly Python, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
What problem a ranked tool list actually solves
Python's developer-tooling space is wide and repetitive. The README counts 270 projects across 17 categories, from 41 linters and style checkers to 43 testing tools to 2 shell-related projects. Anyone starting a new project, or auditing an old one, faces the same question: which of the dozens of linters, formatters, debuggers and packaging tools is still alive and reasonably used? best-of-python-dev answers that with a single page. The README states that all projects are ranked by a project-quality score calculated from metrics automatically collected from GitHub and different package managers. That is the whole proposition: automated collection, weekly regeneration, one sorted list. It is aimed at engineers who want a shortlist fast, and at maintainers who want their project to appear in a category where people are looking. It is not aimed at anyone who wants a recommendation with reasoning attached, because the list does not provide reasoning. Each entry is a name, a one-line description, a licence tag, and install commands.
How the ranking is assembled and what the badges mean
The list is generated, not hand-written. The README points contributors at projects.yaml, which is the file you edit to add or update a project, and the weekly releases (2026.08.13, 2026.08.20, 2026.08.27 in the supplied release feed) are the output of that generation step. Ranking comes from a combined project-quality score shown with medal emoji: ruff carries a gold medal and a score of 35, pylint 30, flake8 29, wemake-python-styleguide 29. The README does not spell out the weights behind that number, only that it draws on GitHub and package-manager metrics. Around the score sits a badge vocabulary that is more informative than the rank itself: a chick for projects less than six months old, a sleeping symbol for six months without activity, a skull for twelve months, arrows for trending up or down, a plus for recently added, and a warning triangle for problems such as a missing or risky licence. Ecosystem markers flag whether a project belongs to the Flake8, Pytest, Pylint, Sphinx or MkDocs families. For a reader, the activity and licence badges are the useful signal. The medal is a summary of numbers you cannot see.
The metadata is the product, not the prose
Each entry follows the same shape, and the shape is worth understanding before you trust a comparison. Take ruff: score 35, MIT, installable with pip install ruff or conda install -c conda-forge ruff, with a monthly PyPI download figure and a last-update timestamp of 27.08.2026. pylint shows score 30, GPL-2.0 flagged with a warning marker, pip install pylint, and a downward trend arrow. flake8 shows score 29, MIT, and a PyPI timestamp of 20.06.2025, which is more than a year behind the ruff timestamp on the same page. That gap is visible in the raw entry without any interpretation, and it is the kind of detail the list is genuinely good at surfacing. What the list does not do is explain why ruff outranks pylint, or whether the download counts are comparable across package managers, or how the score treats a project distributed mainly through conda. Treat each entry as a pointer to a repository plus a small set of timestamps and licence tags, and the list behaves well. Treat the medal as a verdict and you are reading a number whose definition is not published in the README.
Getting it running: clone, install, or read the YAML
There is nothing to build. The list is a repository of Markdown and YAML plus a generated website at python-dev.best-of.org. If you want the rendered page, open the homepage. If you want the data, clone the repository. The README's per-project blocks show the clone form for individual tools, for example git clone https://github.com/charliermarsh/ruff for ruff, but that is the tool's own repository, not this list's. To work with the list itself you clone ml-tooling/best-of-python-dev and open projects.yaml. Contributing follows the same path: the README offers three routes, opening an issue, submitting a pull request, or editing projects.yaml directly through the GitHub edit link. There are no configuration keys, no environment variables and no runtime. The only operational decision is whether you consume the rendered Markdown, the generated site, or the YAML source. For anything programmatic, the YAML is the sensible target, since the Markdown is a rendering of it and the site is a rendering of the Markdown.
Where the list stops being useful
The list is a discovery index and it fails as a decision document. Nothing in the supplied material describes how the quality score is weighted, so two projects a few points apart cannot be meaningfully compared, and a project with a lower score is not worse for your use case. Categories are broad: 43 projects under Testing Tools and 41 under Linters and Style Checkers is a lot to scan, and the one-line descriptions are drawn from the projects themselves, so they inherit whatever marketing language those projects use. The list also cannot tell you whether a tool fits your codebase, your Python version, or your CI budget. A second limitation is structural: a project's position depends on metrics that the project's own maintainers influence, and the README notes that contributions are welcome and that anyone can edit projects.yaml through a pull request. That is normal for curated lists, but it means the ranking reflects what has been submitted and kept current, not a systematic survey. Absence from the list is not evidence that a tool is bad. It may simply never have been added.
The realistic alternative: Awesome Python and plain PyPI search
The obvious alternative is Awesome Python, the long-running community list in the awesome family. The difference is in the mechanism, not the audience. Awesome Python is edited by hand and grouped thematically; it carries no score, no download counts, no last-update timestamps and no activity badges. best-of-python-dev is generated weekly from collected metrics and sorts within each category by a computed number. If you want a stable, human-curated reading list where ordering is editorial, the awesome list is the better fit. If you want to see which of two linters was published to PyPI more recently, or which entries carry a licence warning, best-of-python-dev gives you that in the entry itself. A third option is simply searching PyPI and reading release histories directly, which is slower but avoids trusting any intermediate ranking. None of these replaces reading the tool's own documentation.
Maintenance, licence and what the weekly cadence costs you
The repository is licensed CC-BY-SA-4.0, which is a content licence rather than a software licence, and it is the standard choice for curated lists. It covers the list itself. It does not cover the 270 projects listed, each of which carries its own licence, and the list flags at least one of them: pylint is marked GPL-2.0 with a warning marker, while ruff, flake8 and wemake-python-styleguide are marked MIT. If you copy an entry into a dependency file, the licence tag next to it is the one that matters, and the list is explicit that a warning marker indicates a missing or risky licence. On maintenance, the weekly release cadence is visible in the release feed, and the repository is not archived, so the generated page is likely to stay current. The cost to you is low: there is no dependency to upgrade and no service to run. The cost of the cadence is that a project can move between categories of activity (new, inactive, dead) without anyone writing a sentence about it, so a snapshot you take today may look different next month.
Who should keep this open in a tab
Keep it if you are choosing tooling for a new Python project and want a fast, sorted shortlist with licence and activity signals attached, or if you maintain a tool and want it discoverable in a category people actually browse. Skip it if you need a recommendation with reasoning, or if you are evaluating a single tool in depth, because the list will not carry that weight. The most useful habit with this repository is to read three fields per entry rather than the medal: the licence tag, the last-update timestamp, and the activity badge. Those three are the parts the generator collects and the parts that change your decision.
Editorial conclusion
Use best-of-python-dev as a discovery index and as a machine-readable inventory of Python tooling, especially if you want the projects.yaml file rather than the rendered page. Do not use it as a substitute for evaluating a specific tool, and do not treat the quality score as a verdict. Before relying on any entry, open that project's own repository and check its licence, its last release date, and whether it is marked inactive or dead in the list itself. The first thing to verify is the licence column: pylint is flagged GPL-2.0 in the list while ruff and flake8 are marked MIT, and that difference matters more to adoption than any rank.
Community notes